Method and device for scanning the quality of concrete structures based on signal energy

Abstract

The present invention discloses a method and device for scanning the quality of concrete structures based on signal energy, and performs energy parameter tomography based on N sets of acceleration waveform data, including the following steps: E1. Obtain corresponding N energy parameters according to the acceleration waveform data of the excitation acceleration sensor at one excitation point in each set of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors located at receiving points; E2. Create a virtual propagation line energy propagation line and configure the energy parameters corresponding to each propagation line energy propagation line; E3. Create a cloud map grid; E4. Traverse the propagation line energy propagation lines passing through the cells of the cloud map grid, and mark the energy parameters corresponding to the propagation line energy propagation lines passing through the cell as the elements of the cell; E5. Fill the cell values into the cells, and the cell value is the average value of the elements of the cell; E6. Generate an energy cloud map according to the cell values.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete structure quality inspection, and particularly to a method and device for scanning the quality of concrete structures based on signal energy. Background Art

[0002] The quality inspection of concrete structures is an important technical link in engineering construction. Generally, it is for detecting defects such as internal cavities, non-compaction, and segregation in concrete structures. The common detection method is the elastic wave tomography (CT) method. The main technical parameters relied on by this technology are wave velocities. Generally, the approach is to respectively set an excitation acceleration sensor and a receiving acceleration sensor on two opposite sides of the concrete, tap sequentially along points, and collect a set of data. After multiple taps, multiple sets of data will be obtained. The wave velocities corresponding to different paths are calculated by using the time difference of each group of waveforms and the distances from different points to the tapping points, and then an inversion algorithm such as an iterative reconstruction technique is used to obtain a two-dimensional or three-dimensional equivalent wave velocity distribution contour map. However, concrete structures are generally plate-like structures. According to the principle of the fastest wave, in the case where there are defects inside but the surface is sound for plate-like structures (such as beam slabs, floor slabs, shear walls, concrete panels, etc.), the wave will propagate along the surface of the structure. At this time, since the wave path hardly changes, when imaging the wave velocity, the defects cannot be effectively inverted. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and device for scanning the quality of concrete structures based on signal energy to solve the problems raised in the above background art.

[0004] To solve the above technical problems, the present invention adopts the following solutions:

[0005] In a first aspect, a method for scanning the quality of concrete structures based on signal energy includes the following steps:

[0006] S1. Obtain N groups of acceleration waveform data; each group of acceleration waveform data includes the acceleration waveform data of 1 excitation acceleration sensor located at the excitation point and the acceleration waveform data of N receiving acceleration sensors located at the receiving points. The excitation point and the receiving points are N points respectively located on two symmetric sides or two surfaces of the concrete block to be measured, and N≥2;

[0007] S2. Perform energy parameter tomography based on N groups of acceleration waveform data and / or perform composite imaging of energy parameters and wave velocity parameters based on N groups of acceleration sensing data.

[0008] Performing energy parameter tomography based on N groups of acceleration waveform data includes the following steps:

[0009] E1. Obtain the corresponding N energy parameters according to the acceleration waveform data of the oscillation acceleration sensor at one oscillation point in each group of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors at the receiving points. The N energy parameters form a group of energy data, and a total of N groups of energy data are obtained according to the N groups of acceleration waveform data at the receiving points;

[0010] E2. Create virtual energy propagation lines from N oscillation points to N receiving points respectively, and configure the energy parameters corresponding to each energy propagation line;

[0011] E3. Create a cloud map grid with k rows and L columns;

[0012] E4. Place the energy propagation lines in the cloud map grid, traverse the energy propagation lines passing through the cells in the cloud map grid, and mark the energy parameters corresponding to the energy propagation lines passing through the cell as the elements of the cell;

[0013] E5. Calculate the average of the elements of the cell, and the average value is the cell value;

[0014] E6. Fill the cell value into the cell, and the cell value is the average value of the elements of the cell;

[0015] E7. Generate an energy cloud map according to the cell values.

[0016] The energy parameter is preferably: amplitude ratio or amplitude difference. Amplitude ratio: K i.j = F i.j / F i ; Amplitude difference: K i.j = F i - F i.j ;

[0017] F i.j is the amplitude value of the acceleration waveform data of the receiving acceleration sensor at the jth receiving point in the ith group of acceleration sensing data;

[0018] F i is the amplitude value of the acceleration waveform data of the oscillation acceleration sensor at the oscillation point in the ith group of acceleration sensing data; i takes values from 1 to N, and j takes values from 1 to N.

[0019] The technical problem to be solved by the present invention is: to solve the problem that the traditional wave velocity imaging technology relying on wave velocity characteristics will have the phenomenon of the fastest wave, and the wave propagation will propagate along the sound concrete surface, resulting in no change in the path, and it is impossible to effectively implement elastic wave tomography and effectively invert the defects. The present invention first proposes energy as the observation feature from the technical route level. The energy of the signal is significantly attenuated when propagating in the defective (surface sound) area, so the internal defects of the structure can be effectively inverted through energy attenuation imaging.

[0020] Based on the tomography method of the present invention that uses energy as the observation feature, this technology can be applied to large-volume and large-thickness concrete. The images obtained can clearly reflect the internal defects, casting compactness, and uniformity of the concrete. The present invention innovatively adds energy imaging, resulting in a qualitative improvement in detection accuracy and adaptability. It can be applied to concrete and rock mass structures with double-sided testing conditions such as the zero-block, web, bottom plate, top plate, bearings, piers, columns, dams, diversion tunnels, and buildings of bridges.

[0021] In summary, the present invention uses impact elastic waves as the medium and signal energy as the calculation basis. It conducts a full-range scan of the object to be inspected through cross survey lines, extracts the signal energy from the collected data, and then performs inversion and reconstruction based on the signal energy to obtain a structural quality distribution map that can truly reflect the internal structure, achieving the purpose of detecting the internal quality of the structure.

[0022] The present invention establishes an observation cloud map based on energy loss as a characteristic parameter. Therefore, in principle, the energy at the excitation point minus the energy at the receiving point can be used as the energy parameter. However, since the present invention generally uses a starting hammer to strike at the excitation point to achieve starting, if the striking force of the starting hammer can be ensured to be consistent each time, then the energy at the excitation point (excitation energy) can be ensured to be consistent. From the perspective of the consistency of energy loss, the energy at the receiving point will also be consistent. Due to too many interference factors, it is difficult to ensure that the energy at the excitation point (excitation energy) is consistent each time of striking. Therefore, the present invention can also use the amplitude ratio as the energy parameter. Using the amplitude ratio can eliminate the influence problem caused by inconsistent excitation energy. That is, when the excitation energy is ensured to be consistent each time, the amplitude difference can be used as the energy parameter; if the excitation energy cannot be ensured to be consistent each time, the amplitude ratio can be used as the energy parameter.

[0023] Furthermore, under certain working conditions, the tomography scan results based on wave velocity also have reference significance for the true results. Therefore, the present invention also involves composite imaging. Composite imaging is to combine the energy parameter and the wave velocity parameter. Specifically: the weight method is used to allocate the proportion of the energy parameter and the wave velocity parameter, and finally, a composite based on the proportion allocation of the energy parameter and the wave velocity parameter is obtained. After calculation, a comprehensive value is used as the observation feature, and this comprehensive value is used as the basis for constructing the cloud map. That is, composite imaging is: the wave velocity data is normalized to form a wave velocity factor, and the energy data is normalized to form an energy factor. According to the structural characteristics at the same imaging scale, weights between 0 and 1 are given to each factor to re-image and form the resulting cloud map.

[0024] Performing composite imaging of the energy parameter and the wave velocity parameter based on N groups of acceleration sensing data includes the following steps:

[0025] Z1. Obtain the corresponding N energy parameters and the corresponding N wave velocity parameters according to the acceleration waveform data of the oscillation acceleration sensor at 1 oscillation point in each group of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors at the receiving points. The N energy parameters form 1 group of energy data, and the N wave velocity parameters form 1 group of wave velocity data. A total of N groups of energy data and N groups of wave velocity data are obtained according to the N groups of acceleration waveform data at the receiving points;

[0026] Z2. Create virtual propagation lines from N oscillation points to N receiving points respectively, and configure the energy parameters and wave velocity parameters corresponding to each propagation line;

[0027] Z3. Create a cloud map grid with k rows and L columns;

[0028] Z4. Place the propagation lines in the cloud map grid, traverse the propagation lines passing through the cells in the cloud map grid, and mark the energy parameters and wave velocity parameters corresponding to the propagation lines passing through the cell as the elements of the cell;

[0029] Z5. Calculate the average energy based on the energy parameters in each cell and calculate the average wave velocity based on the wave velocity parameters in each cell;

[0030] Z6. Normalize the average energy within the preset effective energy range to obtain a normalized energy factor, and normalize the average wave velocity within the preset effective wave velocity range to obtain a normalized wave velocity factor;

[0031] Z7. Sum the normalized energy factor and the normalized wave velocity factor with weights configured in the cell, and the sum value is the cell value;

[0032] Z8. Fill the cell value into the cell;

[0033] Z9. Generate a composite cloud map according to the cell values.

[0034] The wave velocity parameter is: wave velocity value, wave velocity value V i.j = D i.j / △t i.j ;

[0035] V i.j is the wave velocity value corresponding to the j-th receiving point in the i-th group of acceleration sensing data;

[0036] D i.j is the length of the propagation line from the oscillation point to the j-th receiving point in the i-th group of acceleration sensing data;

[0037] △t i is the propagation time from the oscillation point to the j-th receiving point in the i-th group of acceleration sensing data;

[0038] △ti = t j -t i ,

[0039] t j is the moment when the acceleration waveform data of the received acceleration sensor at the j-th received point in the i-th group of acceleration sensing data is generated.

[0040] t i is the moment when the acceleration waveform data of the oscillating acceleration sensor at the oscillation point in the i-th group of acceleration sensing data is generated; i ranges from 1 to N, and j ranges from 1 to N.

[0041] The energy parameter is: amplitude ratio or amplitude difference. Amplitude ratio: K i.j = F i.j / F i ; Amplitude difference: K i.j = F i - F i.j ;

[0042] F i.j is the amplitude value of the acceleration waveform data of the received acceleration sensor at the j-th received point in the i-th group of acceleration sensing data;

[0043] F i is the amplitude value of the acceleration waveform data of the oscillating acceleration sensor at the oscillation point in the i-th group of acceleration sensing data; i ranges from 1 to N, and j ranges from 1 to N.

[0044] In Z6, the preset effective energy interval range is: 0 to 0.02, and the preset effective wave speed interval range is determined according to the strength of the concrete structure to be measured. For example: when the concrete block to be measured is a C50 concrete block, the preset effective wave speed interval range is 4200 m / s - 5000 m / s.

[0045] In Z7, the cell value is P X.Y , P X.Y = a * E 归 + b * V 归 , P X.Y is the cell value of the cell in the X-th row and Y-th column, X ranges from 1 to K, Y ranges from 1 to L, a is the weight of the normalized energy factor, b is the weight of the normalized wave speed factor, 0 < a < 1, 0 < b < 1, and a + b = 1; E 归 is the normalized energy factor, V 归 is the normalized wave speed factor.

[0046] On the other hand, the present invention provides a device for scanning the quality of a concrete structure based on signal energy, including:

[0047] One or more displays;

[0048] One or more processors;

[0049] A storage unit for storing one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement the method for scanning the quality of a concrete structure based on signal energy according to any one of claims 1 to 7.

[0050] On the other hand, the present invention provides a device for scanning the quality of a concrete structure based on signal energy, comprising:

[0051] A waveform collector: obtaining N sets of acceleration waveform data; each set of acceleration waveform data includes the acceleration waveform data of 1 vibration acceleration sensor located at the vibration point and the acceleration waveform data of N receiving acceleration sensors located at the receiving points, where the vibration point and the receiving points are: N points respectively located on the symmetric two sides or two surfaces of the concrete block to be measured;

[0052] A tomograph: an energy parameter tomograph for performing energy parameter tomography based on N sets of acceleration waveform data or / and a composite imager for performing composite imaging of energy parameters and wave velocity parameters based on N sets of acceleration sensing data.

[0053] The energy parameter tomograph includes:

[0054] An energy data converter: obtaining corresponding N energy parameters according to the acceleration waveform data of 1 vibration acceleration sensor at the vibration point and the acceleration waveform data of N receiving acceleration sensors at the receiving points in each set of acceleration waveform data, the N energy parameters form 1 set of energy data, and a total of N sets of energy data are obtained according to the N sets of acceleration waveform data of the receiving points;

[0055] An energy propagation line generator: creating virtual propagation line energies from N vibration points to N receiving points respectively, and configuring the energy parameters corresponding to each propagation line energy;

[0056] A cloud map grid generator: creating a cloud map grid with k rows and L columns;

[0057] An element recorder: placing the propagation line energy in the cloud map grid, traversing the propagation line energy passing through the cells in the cloud map grid, and marking the energy parameter corresponding to the propagation line energy passing through the cell as the element of the cell;

[0058] An average calculator: calculating the average of the elements of the cell, and the average value is the cell value;

[0059] A cloud map grid generator: filling the cell value into the cell, and the cell value is the average value of the elements of the cell;

[0060] Cloud map generator: Generates an energy cloud map based on cell values.

[0061] Composite imager: Includes:

[0062] Energy data and wave velocity data converter: Obtains corresponding N energy parameters and corresponding N wave velocity parameters based on the acceleration waveform data of the oscillation acceleration sensor at 1 oscillation point in each group of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors located at the receiving points. The N energy parameters form 1 group of energy data, and the N wave velocity parameters form 1 group of wave velocity data. A total of N groups of energy data and N groups of wave velocity data are obtained based on the N groups of acceleration waveform data at the receiving points;

[0063] Propagation line generator: Creates virtual propagation lines from N oscillation points to N receiving points respectively, and configures the corresponding energy parameters and wave velocity parameters for each propagation line;

[0064] Cloud map grid generator: Creates a cloud map grid with k rows and L columns;

[0065] Element recorder: Places the propagation lines in the cloud map grid, traverses the propagation lines passing through the cells in the cloud map grid, and marks the energy parameters and wave velocity parameters corresponding to the propagation lines passing through the cell as the elements of the cell;

[0066] Average calculator: Calculates the energy average based on the energy parameters in each cell and calculates the wave velocity average based on the wave velocity parameters in each cell;

[0067] Normalization converter: Normalizes the energy average within a preset effective energy interval range to obtain a normalized energy factor, and normalizes the wave velocity average within a preset effective wave velocity interval range to obtain a normalized wave velocity factor;

[0068] Weighted summation calculator: Sums the normalized energy factor and the normalized wave velocity factor with weights configured in the cell, and the summation value is the cell value;

[0069] Cloud map grid generator: Fills the cell values into the cells;

[0070] Cloud map generator: Generates an energy cloud map based on cell values.

[0071] Advantages of the present invention: The present invention utilizes the energy characteristics to solve the technical problem that effective tomographic imaging cannot be performed using wave velocity in the case of large volume and large thickness dimensions. Compared with the existing wave velocity tomographic imaging technology, this method has higher adaptability, more accurate results, and higher precision. Brief Description of the Drawings

[0072] Figure 1 It is a circuit schematic diagram of the detection system;

[0073] Figure 2 Schematic diagram of the principle of cross survey lines;

[0074] Figure 3 Schematic diagram of virtual wave velocity propagation lines.

[0075] Figure 4 Schematic diagram of virtual propagation line energy propagation lines.

[0076] Figure 5 Schematic diagram of the superposition of cloud map grids and propagation lines.

[0077] Figure 6 Schematic diagram of a set of acceleration waveform data.

[0078] Figure 7 Schematic diagram of the structure of a test model.

[0079] Figure 8 Physical diagram of a test model.

[0080] Figure 9 Energy cloud map obtained according to the present invention.

[0081] Figure 10 Wave velocity cloud map obtained by wave velocity tomography.

[0082] Figure 11 Composite cloud map obtained according to the present invention.

[0083] Figure 12 Flow schematic diagram of the present invention.

[0084] The reference numerals in the figure respectively represent: 1, concrete block to be measured; 2, scanning analyzer; 11, excitation point; 12, reception point; 21, excitation acceleration sensor; 22, reception acceleration sensor; 23, excitation hammer. Specific embodiments

[0085] The present invention will be further described in detail below in conjunction with embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0086] Embodiment 1

[0087] First aspect, a method for scanning the quality of concrete structures based on signal energy, comprising the following steps:

[0088] S1. Obtain N groups of acceleration waveform data; each group of acceleration waveform data includes the acceleration waveform data of one excitation acceleration sensor 21 located at the excitation point 11 and the acceleration waveform data of N reception acceleration sensors 22 located at the reception points 12. The excitation point 11 and the reception points 12 are: N equally spaced points respectively located on the symmetric two sides of the concrete block to be measured;

[0089] Among them, referring to the attached Figure 1 , this figure is observed from a top-down perspective. Measuring points are marked on the left and right sides of the concrete block 1 to be measured. The measuring points on the left and right sides are consistent in height and symmetrical left and right. The one on the left is the oscillation point 11, and the one on the right is the receiving point 12. Among them, N = 8 receiving acceleration sensors 22 are fixed at the receiving point on the right, and there is 1 oscillation acceleration sensor 21 on the left. This oscillation acceleration sensor 21 is not fixed. When the oscillation hammer 23 strikes the first oscillation point 11 for the first time, the oscillation acceleration sensor 21 is located at a position adjacent to the first oscillation point 11. At this time, 1 set of acceleration waveform data is obtained (the acceleration waveform data of 8 receiving acceleration sensors 22 + the acceleration waveform data of 1 oscillation acceleration sensor 21); repeat the next oscillation point 11 to obtain a new set of acceleration waveform data; until all 8 oscillation points on the left are detected. Therefore, 8 sets of acceleration waveform data will be obtained. Referring to the attached Figure 6 , the 8 acceleration waveform data from top to bottom are the acceleration waveform data of the receiving acceleration sensors 22, and the last acceleration waveform data is the acceleration waveform data of the oscillation acceleration sensor 21, with a total of 8 sets. Generally, N equally spaced points are distributed at an interval of 0.2 m or 0.3 m.

[0090] According to the distribution in the attached Figure 1 , perform on-site oscillation to generate raw data, and then the scanning analyzer 2 records the acceleration waveform data. Subsequently, the scanning analyzer 2 starts to execute the imaging mode. It can perform the energy parameter tomography mode or the composite imaging mode.

[0091] S2. Perform energy parameter tomography based on N sets of acceleration waveform data and / or perform composite imaging of energy parameters and wave velocity parameters based on N sets of acceleration sensing data.

[0092] Performing energy parameter tomography based on N sets of acceleration waveform data includes the following steps:

[0093] E1. Obtain the corresponding N energy parameters according to the acceleration waveform data of the oscillation acceleration sensor at 1 oscillation point in each set of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors at the receiving points. The N energy parameters form 1 set of energy data, and a total of N sets of energy data are obtained according to the N sets of acceleration waveform data at the receiving points;

[0094] E2. Create virtual energy propagation lines from N oscillation points to N receiving points respectively, and configure the energy parameters corresponding to each energy propagation line; referring to the attached Figure 3 , the attached Figure 3 is 1 set of energy propagation lines, where K represents the energy parameter.

[0095] E3. Create a cloud map grid with k rows and L columns;

[0096] E4. Refer to the appendix Figure 5 , place the energy propagation lines in the cloud map grid, traverse the energy propagation lines passing through the cells in the cloud map grid, and mark the energy parameters corresponding to the energy propagation lines passing through the cell as the elements of the cell; refer to the appendix Figure 5 , the number of cells in this cloud map grid is 80, distributed in 8 rows and 10 columns. The P in the figure represents the cell value corresponding to the cell. Among them, there are 8 energy propagation lines passing through the cell in the first row and first column, 5 energy propagation lines passing through the cell in the first row and first column... Traverse in sequence and record the energy propagation lines passing through each cell.

[0097] E5. Take the average of the elements of the cell, and the average value is the cell value;

[0098] E6. Fill the cell value into the cell, and the cell value is the average value of the elements of the cell; according to the energy propagation lines of each cell recorded in E4 above, taking the cells in the first row as an example, the corresponding cell values are obtained as follows: P1,1 = (K 1.1 + K 1.2 + … + K 1.8 ) / 8; P1,2 = (K 1.1 + K 1.2 + … + K 1.5 ) / 5; P1,3 = (K 1.1 + K 1.2 + K 1.3 ) / 3; P1,4 = (K 1.1 + K 1.2 ) / 2; P1,5 = (K 1.1 + K 1.2 ) / 2; P1,6 = (K 1.1 + K 2.1 ) / 2; P1,7 = (K 1.1 + K 2.1 ) / 2; P1,8 = (K 1.1 + K 2.1 + K 3.1 ) / 3; P1,9 = (K 1.1 + K 2.1 + … + K 5.1 ) / 5; P1,10 = (K 1.1 + K 2.2 + … + K 8.1 ) / 8.

[0099] E7. Generate an energy cloud map based on the cell values.

[0100] The energy parameter is preferably: amplitude ratio or amplitude difference, amplitude ratio: K i.j= F i.j / F i ; Amplitude difference: K i.j = F i -F i. j;

[0101] F i.j is the amplitude value of the acceleration waveform data of the receiving acceleration sensor 22 of the j-th receiving point 12 in the i-th group of acceleration sensing data;

[0102] F i is the amplitude value of the acceleration waveform data of the transmitting acceleration sensor 21 of the transmitting point 11 in the i-th group of acceleration sensing data; i ranges from 1 to N, and j ranges from 1 to N.

[0103] The technical problem to be solved by the present invention is that: in the traditional wave velocity imaging technology relying on wave velocity characteristics, the phenomenon of the fastest wave will occur, and the wave propagation will propagate along the surface of sound concrete, resulting in no change in the path, unable to effectively realize elastic wave tomography imaging and unable to effectively invert defects. The present invention first proposes energy as an observation feature from the technical route level. The energy of the signal is significantly attenuated when propagating in a defective (surface sound) area, so the internal defects of the structure can be effectively inverted through energy attenuation imaging.

[0104] Based on the tomography imaging method of the present invention with energy as the observation feature, this technology can adapt to large-volume and large-thickness concrete, and the imaged picture can clearly reflect the internal defects, pouring compactness, and uniformity of the concrete. The present invention innovatively adds energy imaging, and there has been a qualitative improvement in detection accuracy and adaptability. It can adapt to concrete and rock mass structures with double-sided testing conditions such as the zero block, web, bottom plate, top plate, bearing, pier, column, dam, diversion tunnel, and building of the bridge.

[0105] In summary, the present invention uses impact elastic waves as the medium, signal energy as the calculation basis, performs a full-range scan of the object to be inspected through cross measuring lines, extracts signal energy from the collected data, and then performs inversion and reconstruction based on the signal energy to obtain a structural quality distribution map that can truly reflect its internal structure, achieving the purpose of detecting the internal quality of the structure.

[0106] The present invention establishes an observation cloud map based on energy loss as a characteristic parameter. Therefore, in principle, the energy at the oscillation point minus the energy at the receiving point can be used as the energy parameter. However, since the present invention generally uses a starting hammer to strike at the oscillation point to achieve starting, if the striking force of the starting hammer can be ensured to be consistent each time, then the energy (excitation energy) at the oscillation point can be ensured to be consistent. From the perspective of the consistency of energy loss, the energy at the receiving point will also be consistent. Due to too many interference factors, it is difficult to ensure that the energy (excitation energy) at the oscillation point is consistent each time of striking. Therefore, the present invention can also use the amplitude ratio as the energy parameter. By using the amplitude ratio, the influence problem due to inconsistent excitation energy can be excluded. That is, when the excitation energy is ensured to be consistent each time, the amplitude difference can be used as the energy parameter. If the excitation energy cannot be ensured to be consistent each time, the amplitude ratio can be used as the energy parameter.

[0107] Furthermore, under certain working conditions, the tomographic scanning results based on wave velocity also have reference significance for the true results. Therefore, the present invention also relates to composite imaging. Composite imaging is to composite the energy parameter and the wave velocity parameter. Specifically: the proportion of the energy parameter and the wave velocity parameter is allocated by the weighting method, and finally the composite allocation based on the proportion of the energy parameter and the wave velocity parameter is obtained. After calculation, a comprehensive value is obtained as the observation feature, and this comprehensive value is used as the basis for constructing the cloud map. That is, composite imaging is: the wave velocity data is normalized to form a wave velocity factor, and the energy data is normalized to form an energy factor. According to the structural characteristics at the same imaging scale, a result cloud map is formed by re-imaging with weights between 0 and 1 for each factor.

[0108] The composite imaging of the energy parameter and the wave velocity parameter based on N groups of acceleration sensing data includes the following steps:

[0109] Z1. Obtain the corresponding N energy parameters and the corresponding N wave velocity parameters according to the acceleration waveform data of the oscillation acceleration sensor 21 at one oscillation point 11 in each group of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors 22 located at the receiving points 12. The N energy parameters form a group of energy data, and the N wave velocity parameters form a group of wave velocity data. A total of N groups of energy data and N groups of wave velocity data are obtained according to the N groups of acceleration waveform data of the receiving points.

[0110] Z2. Create virtual propagation lines from N oscillation points 11 to N receiving points 12 respectively, and configure the corresponding energy parameter and wave velocity parameter for each propagation line; see the appendix Figure 3 and the appendix Figure 4 .

[0111] Z3. Create a cloud map grid with k rows and L columns;

[0112] Z4. Place the propagation line in the cloud map grid, traverse the propagation lines passing through the cells in the cloud map grid, and mark the energy parameters and wave speed parameters corresponding to the propagation lines passing through the cell as the elements of the cell;

[0113] Z5. Calculate the average energy based on the energy parameters in each cell and calculate the average wave speed based on the wave speed parameters in each cell; see Appendix Figure 5 , the number of cells in the cloud map grid is 80, distributed in 8 rows and 10 columns. P in the figure represents the cell value corresponding to the cell. Among them, there are 8 propagation lines passing through the cell in the first row and first column, 5 propagation lines passing through the cell in the first row and first column... Traverse in turn and record the propagation lines passing through each cell.

[0114] According to the propagation lines of each cell recorded in Z4 above, taking the cells in the first row as an example, the corresponding cell values are:

[0115] Average energy: P1,1 = (K 1.1 + K 1.2 +... + K 1.8 ) / 8; P1,2 = (K 1.1 + K 1.2 +... + K 1.5 ) / 5; P1,3 = (K 1.1 + K 1.2 + K 1.3 ) / 3; P1,4 = (K 1.1 + K 1.2 ) / 2; P1,5 = (K 1.1 + K 1.2 ) / 2; P1,6 = (K 1.1 + K 2.1 ) / 2; P1,7 = (K 1.1 + K 2.1 ) / 2; P1,8 = (K 1.1 + K 2.1 + K 3.1 ) / 3; P1,9 = (K 1.1 + K 2.1 +... + K 5.1 ) / 5; P1,10 = (K 1.1 + K 2.2 +... + K 8.1 ) / 8.

[0116] Average wave speed: P1,1 = (V 1.1 + V 1.2 +... + V 1.8 ) / 8; P1,2 = (V 1.1 + V 1.2 +... + V 1.5) / 5; P1,3 = (V 1.1 + V 1.2 + V 1.3 ) / 3; P1,4 = (V 1.1 + V 1.2 ) / 2; P1,5 = (V 1.1 + V 1.2 ) / 2; P1,6 = (V 1.1 + V 2.1 ) / 2; P1,7 = (V 1.1 + V 2.1 ) / 2; P1,8 = (V 1.1 + V 2.1 + V 3.1 ) / 3; P1,9 = (V 1.1 + V 2.1 + … + V 5.1 ) / 5; P1,10 = (V 1.1 + V 2.2 + … + V 8.1 ) / 8。

[0117] Z6. Normalize the energy average value within the preset effective energy range to obtain a normalized energy factor, and normalize the wave speed average value within the preset effective wave speed range to obtain a normalized wave speed factor;

[0118] Z7. Sum the normalized energy factor and the normalized wave speed factor with weights configured in the cell, and the sum value is the cell value;

[0119] Z8. Fill the cell value into the cell;

[0120] Z9. Generate a composite cloud map based on the cell value.

[0121] The wave speed parameter is: wave speed value, wave speed value V i.j = D i.j / △t i.j ;

[0122] V i.j is the wave speed value corresponding to the j-th receiving point 12 in the i-th group of acceleration sensing data;

[0123] D i.j is the length of the propagation line from the oscillation point 11 to the j-th receiving point 12 in the i-th group of acceleration sensing data;

[0124] △t i is the propagation time from the oscillation point 11 to the j-th receiving point 12 in the i-th group of acceleration sensing data;

[0125] △t i = t j - ti ,

[0126] t j is the moment when the acceleration waveform data of the receiving acceleration sensor 22 at the j-th receiving point 12 in the i-th group of acceleration sensing data is generated,

[0127] t i is the moment when the acceleration waveform data of the transmitting acceleration sensor 22 at the transmitting point 11 in the i-th group of acceleration sensing data is generated; i ranges from 1 to N, and j ranges from 1 to N.

[0128] The energy parameter is: amplitude ratio or amplitude difference. Amplitude ratio: K i.j = F i.j / F i ; Amplitude difference: K i.j = F i - F i.j ;

[0129] F i.j is the amplitude value of the acceleration waveform data of the receiving acceleration sensor 22 at the j-th receiving point 12 in the i-th group of acceleration sensing data;

[0130] F i is the amplitude value of the acceleration waveform data of the transmitting acceleration sensor 21 at the transmitting point 11 in the i-th group of acceleration sensing data; i ranges from 1 to N, and j ranges from 1 to N.

[0131] In Z6, the preset effective energy interval range is: 0 to 0.02, and the preset effective wave velocity interval range is determined according to the strength of the concrete structure to be measured. For example: when the concrete block to be measured is a C50 concrete block, the preset effective wave velocity interval range is 4200 m / s - 5000 m / s.

[0132] In Z7, the cell value is P X.Y , P X.Y = a * E 归 + b * V 归 , P X.Y is the cell value of the cell in the X-th row and Y-th column, X ranges from 1 to K, Y ranges from 1 to L, a is the weight of the normalized energy factor, b is the weight of the normalized wave velocity factor, 0 < a < 1, 0 < b < 1, and a + b = 1; E 归 is the normalized energy factor, V 归 is the normalized wave velocity factor.

[0133] Example 2

[0134] See Appendix Figure 7 to Appendix Figure 11 .

[0135] This embodiment is to verify that the present invention has achieved better detection effects than the wave velocity tomography technology by using the energy tomography technology and the composite tomography technology.

[0136] See the appendix Figure 7 , the appendix Figure 7 is the designed defect model. Defect model description:

[0137] Model size: length * width * height: 1m * 1m * 0.3m;

[0138] Concrete strength: C30;

[0139] Defect 1: Cylindrical opening defect, diameter 0.1m; Defect category: surface defect.

[0140] Defect 2: Cubical opening defect, side length 0.4m; Defect category: surface defect.

[0141] Defect 3: Cubical defect, located inside the model, side length 0.3m; Defect category: internal defect.

[0142] See the appendix Figure 9 , the appendix Figure 9 is the cloud map obtained by using the above energy characteristics. It can be seen from this cloud map that whether it is a surface defect or an internal defect, the present invention can effectively identify them. It can be seen from this cloud map that the identification effect of the method of the present invention can effectively detect from aspects such as area and position, and it has corresponding consistency with the area and position of the actual defect.

[0143] See the appendix Figure 10 , the appendix Figure 9 is the cloud map obtained by using the wave velocity characteristics. It can be seen from this cloud map that it can only effectively detect surface defects with a larger area (the area of defect 2 is larger than that of defect 1). It cannot effectively detect internal defects and smaller areas of surface defects.

[0144] Therefore, based on the above effects, the present invention creatively proposes to construct a cloud map using energy characteristics, which has outstanding and unexpected technical effect contributions.

[0145] See the appendix Figure 11 , it can detect defect 1, defect 2, and defect 3, but the area is not obvious and the correspondence is poor. It is necessary to correct the parameters in the composite process to adjust a better effect.

[0146] It can be seen from the above cloud map. The method of constructing a cloud map with the single energy characteristic of the present invention has the best technical effect.

[0147] On the other hand, the present invention provides a device for scanning the quality of a concrete structure based on signal energy, including:

[0148] One or more displays;

[0149] One or more processors;

[0150] A storage unit for storing one or more programs, which when executed by the one or more processors, enable the one or more processors to implement the method for scanning the quality of a concrete structure based on signal energy according to any one of claims 1 to 7.

[0151] On the other hand, the present invention provides a device for scanning the quality of a concrete structure based on signal energy, including:

[0152] A waveform collector: obtaining N groups of acceleration waveform data; each group of acceleration waveform data includes the acceleration waveform data of 1 vibration acceleration sensor 21 located at the vibration point 11 and the acceleration waveform data of N receiving acceleration sensors 22 located at the receiving points 12. The vibration point 11 and the receiving points 12 are: N equally spaced points respectively located on the symmetric two sides of the concrete block to be measured;

[0153] A tomograph: an energy parameter tomograph for performing energy parameter tomography based on N groups of acceleration waveform data or / and a composite imager for performing composite imaging of energy parameters and wave velocity parameters based on N groups of acceleration sensing data.

[0154] The energy parameter tomograph includes:

[0155] An energy data converter: obtaining corresponding N energy parameters according to the acceleration waveform data of 1 vibration acceleration sensor 21 at the vibration point 11 and the acceleration waveform data of N receiving acceleration sensors 22 at the receiving points 12 in each group of acceleration waveform data. The N energy parameters form 1 group of energy data, and a total of N groups of energy data are obtained according to the N groups of acceleration waveform data of the receiving points;

[0156] An energy propagation line generator: creating virtual energy propagation lines from N vibration points 11 to N receiving points 12 respectively, and configuring the energy parameters corresponding to each energy propagation line;

[0157] A cloud map grid generator: creating a cloud map grid with k rows and L columns;

[0158] An element recorder: placing the energy propagation lines in the cloud map grid, traversing the energy propagation lines passing through the cells in the cloud map grid, and marking the energy parameters corresponding to the energy propagation lines passing through the cell as the elements of the cell;

[0159] An average calculator: calculating the average of the elements of the cell, and the average value is the cell value;

[0160] Cloud Map Grid Generator: Fill the cell values into the cells, where the cell value is the average value of the elements of the cell;

[0161] Cloud Map Generator: Generate an energy cloud map based on the cell values.

[0162] Composite Imager: including:

[0163] Energy Data and Wave Velocity Data Converter: Obtain the corresponding N energy parameters and the corresponding N wave velocity parameters according to the acceleration waveform data of the oscillation acceleration sensor 21 at one oscillation point 11 in each group of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors 22 located at the receiving points 12. The N energy parameters form a group of energy data, and the N wave velocity parameters form a group of wave velocity data. A total of N groups of energy data and N groups of wave velocity data are obtained according to the N groups of acceleration waveform data of the receiving points;

[0164] Propagation Line Generator: Create virtual propagation lines from N oscillation points 11 to N receiving points 12 respectively, and configure the energy parameters and wave velocity parameters corresponding to each propagation line;

[0165] Cloud Map Grid Generator: Create a cloud map grid with k rows and L columns;

[0166] Element Recorder: Place the propagation lines in the cloud map grid, traverse the propagation lines passing through the cells in the cloud map grid, and mark the energy parameters and wave velocity parameters corresponding to the propagation lines passing through the cell as the elements of the cell;

[0167] Average Calculator: Calculate the energy average value based on the energy parameters in each cell and calculate the wave velocity average value based on the wave velocity parameters in each cell;

[0168] Normalization Converter: Normalize the energy average value within a preset effective energy interval range to obtain a normalized energy factor, and normalize the wave velocity average value within a preset effective wave velocity interval range to obtain a normalized wave velocity factor;

[0169] Weighted Summation Calculator: Sum the normalized energy factor and the normalized wave velocity factor with weights configured in the cell, and the summation value is the cell value;

[0170] Cloud Map Grid Generator: Fill the cell values into the cells;

[0171] Cloud Map Generator: Generate an energy cloud map based on the cell values.

Claims

1. A method for scanning the quality of concrete structures based on signal energy, characterized in that, Including the following steps: S1. Obtain N groups of acceleration waveform data; each group of acceleration waveform data includes the acceleration waveform data of 1 vibration acceleration sensor (21) located at the vibration point (11) and the acceleration waveform data of N receiving acceleration sensors (22) located at the receiving points (12). The vibration point (11) and the receiving points (12) are N points respectively located on the symmetric two sides or two surfaces of the concrete block to be measured, and N≥2; S2. Perform energy parameter tomography based on N groups of acceleration waveform data or / and perform composite imaging of energy parameters and wave velocity parameters based on N groups of acceleration sensing data; Among them, performing energy parameter tomography based on N groups of acceleration waveform data includes the following steps: E1. Obtain the corresponding N energy parameters according to the acceleration waveform data of 1 vibration acceleration sensor (21) at the vibration point (11) and the acceleration waveform data of N receiving acceleration sensors (22) at the receiving points (12) in each group of acceleration waveform data. The N energy parameters form 1 group of energy data, and a total of N groups of energy data are obtained according to the N groups of acceleration waveform data of the receiving points; E2. Create virtual energy propagation lines from N vibration points (11) to N receiving points (12) respectively, and configure the energy parameters corresponding to each energy propagation line; E3. Create a cloud map grid with k rows and L columns; E4. Place the energy propagation lines in the cloud map grid, traverse the energy propagation lines passing through the cells in the cloud map grid, and mark the energy parameters corresponding to the energy propagation lines passing through the cell as the elements of the cell; E5. Calculate the average value of the elements of the cell, and the average value is the cell value; E6. Fill the cell value into the cell, and the cell value is the average value of the elements of the cell; E7. Generate an energy cloud map according to the cell value; The energy parameter is specifically expressed as: amplitude ratio or amplitude difference. Amplitude ratio: K i.j =F i.j / F i ; Amplitude difference: K i.j =Fi - F i.j ; F i.j is the amplitude value of the acceleration waveform data of the received acceleration sensor (22) at the j-th received point (12) in the i-th group of acceleration sensing data; F i is the amplitude value of the acceleration waveform data of the oscillation acceleration sensor (21) at the oscillation point (11) in the i-th group of acceleration sensing data; i ranges from 1 to N, and j ranges from 1 to N.

2. The method for scanning the quality of concrete structures based on signal energy according to claim 1, characterized in that, Performing composite imaging of energy parameters and wave velocity parameters based on N groups of acceleration sensing data includes the following steps: Z1. Obtain the corresponding N energy parameters and the corresponding N wave velocity parameters according to the acceleration waveform data of 1 vibration acceleration sensor (21) at the vibration point (11) and the acceleration waveform data of N receiving acceleration sensors (22) at the receiving points (12) in each group of acceleration waveform data. The N energy parameters form 1 group of energy data, and the N wave velocity parameters form 1 group of wave velocity data. A total of N groups of energy data and N groups of wave velocity data are obtained according to the N groups of acceleration waveform data of the receiving points; Z2. Create virtual propagation lines from N vibration points (11) to N receiving points (12) respectively, and configure the energy parameters and wave velocity parameters corresponding to each propagation line; Z3. Create a cloud map grid with k rows and L columns; Z4. Place the propagation lines in the cloud map grid, traverse the propagation lines passing through the cells in the cloud map grid, and mark the energy parameters and wave velocity parameters corresponding to the propagation lines passing through the cell as the elements of the cell; Z5. Calculate the energy average value based on the energy parameters in each cell and calculate the wave velocity average value based on the wave velocity parameters in each cell; Z6. Normalize the energy average value within a preset effective energy range to obtain a normalized energy factor, and normalize the wave speed average value within a preset effective wave speed range to obtain a normalized wave speed factor; Z7. Sum the normalized energy factor and the normalized wave speed factor with configured weights in the cell, and the sum value is the cell value; Z8. Fill the cell value into the cell; Z9. Generate a composite cloud map based on the cell value.

3. The method for scanning the quality of concrete structures based on signal energy according to claim 2, characterized in that, The wave velocity parameter is: wave velocity value, wave velocity value V i.j = D i.j / △t i.j ; V i.j is the wave velocity value corresponding to the j-th received point (12) in the i-th group of acceleration sensing data; D i.j is the length of the propagation line from the oscillation point (11) to the j-th receiving point (12) in the i-th group of acceleration sensing data; △t i is the propagation time from the oscillation point (11) to the j-th receiving point (12) in the i-th group of acceleration sensing data; △ti = tj - ti, t j is the time when the acceleration waveform data of the received acceleration sensor (22) at the j-th received point (12) in the i-th group of acceleration sensing data is generated. t i is the time when the acceleration waveform data of the oscillation acceleration sensor (21) at the oscillation point (11) is generated in the acceleration sensing data of the i-th group; i ranges from 1 to N, and j ranges from 1 to N.

4. The method for scanning the quality of concrete structures based on signal energy according to claim 2, characterized in that, In Z6, the preset effective energy range is: 0 to 0.02, and the preset effective wave speed range is determined according to the strength of the concrete structure to be measured.

5. The method for scanning the quality of concrete structures based on signal energy according to claim 2, wherein In Z7, the cell value is P X.Y , P X.Y =a*E 归 +b*V 归 , where PX.Y is the cell value of the cell in the X-th row and Y-th column, X ranges from 1 to K, Y ranges from 1 to L, a is the weight of the normalized energy factor, b is the weight of the normalized wave speed factor, 0 < a < 1, 0 < b < 1, and a + b = 1; E 归 is the normalized energy factor, and V 归 is the normalized wave speed factor.

6. An apparatus for scanning the quality of concrete structures based on signal energy, wherein Including: One or more displays; One or more processors; A storage unit for storing one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement the method for scanning the quality of a concrete structure based on signal energy according to any one of claims 1 to 5.

7. An apparatus for scanning the quality of concrete structures based on signal energy for implementing the method for scanning the quality of concrete structures based on signal energy according to any one of claims 1-5, wherein Including: A waveform collector: obtaining N sets of acceleration waveform data; Each set of acceleration waveform data includes the acceleration waveform data of 1 vibration acceleration sensor (21) located at the vibration point (11) and the acceleration waveform data of N receiving acceleration sensors (22) located at the receiving points (12). The vibration point (11) and the receiving points (12) are: N points respectively located on the symmetric two sides or two faces of the concrete block to be measured, and N≥2; A tomograph: an energy parameter tomograph for performing energy parameter tomography based on N sets of acceleration waveform data or / and a composite imager for performing composite imaging of energy parameters and wave speed parameters based on N sets of acceleration sensor data.

8. The apparatus for scanning the quality of concrete structures based on signal energy according to claim 7, wherein The energy parameter tomograph includes: An energy data converter: obtaining corresponding N energy parameters according to the acceleration waveform data of 1 vibration acceleration sensor (21) at the vibration point (11) and the acceleration waveform data of N receiving acceleration sensors (22) at the receiving points (12) in each set of acceleration waveform data. The N energy parameters form 1 set of energy data, and a total of N sets of energy data are obtained according to the N sets of acceleration waveform data of the receiving points; An energy propagation line generator: creating virtual energy propagation lines from N vibration points (11) to N receiving points (12) respectively, and configuring the energy parameters corresponding to each energy propagation line; A cloud map grid generator: creating a cloud map grid with k rows and L columns; An element recorder: placing the energy propagation lines in the cloud map grid, traversing the energy propagation lines passing through the cells in the cloud map grid, and marking the energy parameters corresponding to the energy propagation lines passing through the cell as the elements of the cell; An average calculator: calculating the average of the elements of the cell, and the average value is the cell value; A cloud map grid generator: filling the cell value into the cell, and the cell value is the average value of the elements of the cell; A cloud map generator: generating an energy cloud map according to the cell value; The composite imager includes: Energy data and wave velocity data converter: Obtain corresponding N energy parameters and corresponding N wave velocity parameters based on the acceleration waveform data of the oscillation acceleration sensor (21) at one oscillation point (11) in each group of acceleration waveform data and the acceleration waveform data of N receiving acceleration sensors (22) located at the receiving points (12). The N energy parameters form a group of energy data, and the N wave velocity parameters form a group of wave velocity data. A total of N groups of energy data and N groups of wave velocity data are obtained according to the N groups of acceleration waveform data at the receiving points; Propagation line generator: Create virtual propagation lines from N oscillation points (11) to N receiving points (12) respectively, and configure the energy parameters and wave velocity parameters corresponding to each propagation line; Contour map grid generator: Create a contour map grid with k rows and L columns; Element recorder: Place the propagation lines in the contour map grid, traverse the propagation lines passing through the cells in the contour map grid, and mark the energy parameters and wave velocity parameters corresponding to the propagation lines passing through the cell as the elements of the cell; Average calculator: Calculate the energy average based on the energy parameters in each cell and calculate the wave velocity average based on the wave velocity parameters in each cell; Normalization converter: Normalize the energy average within a preset effective energy interval range to obtain a normalized energy factor, and normalize the wave velocity average within a preset effective wave velocity interval range to obtain a normalized wave velocity factor; Weighted summation calculator: Sum the normalized energy factor and the normalized wave velocity factor with weights configured in the cell, and the sum value is the cell value; Contour map grid generator: Fill the cell value into the cell; Contour map generator: Generate an energy contour map according to the cell value.

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